NSERC CREATE in ecology, evolution and environmental science: The Living Data Project

NSERC CREATE 在生态学、进化论和环境科学领域的创造：生命数据项目

• 批准号: 543234-2020
• 负责人: Srivastava, DianeDS
• 金额: $ 21.86万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Training Experience
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=766110
• 关键词: NSERC; CREATE; ecology; evolution; environmental

The rapid rise of information technologies coincides with a period of dramatic change in the Earth's ecosystems. We have the potential to harness the power of this data revolution to understand how species and ecosystems will be affected by global drivers of change such as climate, land use, pollution and biological invasions, and mitigate against these effects. However, this potential can only be realized if we: (1) rescue historical data in ecology, evolution and environmental science (for simplicity, EEE) that set baselines for change, often collected before today's data management standards and therefore at high risk of being lost; and (2) train the EEE researchers of tomorrow in the necessary skills to manage and synthesize large amounts of relevant data, and then to analyse these complex datasets in collaborative teams. Employers are now requiring this new skillset, which applies tools from data science, archival science and team management to EEE-specific tasks. There is a cultural shift underway that recognizes that the most productive researchers incorporate data and collaboration skills at every step in their reproducible scientific workflow, and both academic and non-academic employers are prioritizing such skills in hiring. In our proposed training program, we will first formally teach EEE graduate students skills in data management, synthesis statistics and collaboration, providing a new national certification in these competencies. We will then strategically pair students with willing senior researchers or organizations holding historical EEE datasets of high importance to our partners in government (six), non-profit organizations (six), and biological field stations (three), but which were collected prior to current data management standards. Preserving these datasets will require the specialized data management tools we have taught the students, and the high societal value of this task will be motivating. Trainees will then collaboratively analyse the datasets, using their new teamwork and synthesis skills. The result will be a new generation of scientists with cutting-edge training, equipped with the historical data needed to advance our understanding of global change.

信息技术的迅速崛起与地球生态系统的急剧变化相吻合。我们有潜力利用这场数据革命的力量，了解物种和生态系统将如何受到气候、土地利用、污染和生物入侵等全球变化驱动因素的影响，并减轻这些影响。然而，这种潜力只有在我们：（1）抢救生态学、进化论和环境科学中的历史资料时才能实现（为简单起见，称为“数据库”），为变化设定基线，这些基线通常是在今天的数据管理标准之前收集的，因此有很高的丢失风险;以及（2）培训未来的计算机科学研究人员掌握管理和综合大量相关数据的必要技能，然后在协作团队中分析这些复杂的数据集。雇主现在需要这种新的技能，将数据科学，档案科学和团队管理工具应用于EE特定的任务。目前正在发生一种文化转变，认识到最有成效的研究人员在其可复制的科学工作流程的每一步都融入了数据和协作技能，学术和非学术雇主都在招聘时优先考虑这些技能。在我们提出的培训计划中，我们将首先正式教授研究生在数据管理，综合统计和协作方面的技能，并在这些能力方面提供新的国家认证。然后，我们将战略性地将学生与愿意的高级研究人员或组织进行配对，这些研究人员或组织持有对我们在政府（六个），非营利组织（六个）和生物野外站（三个）的合作伙伴非常重要的历史数据集，但这些数据集是在当前数据管理标准之前收集的。保存这些数据集将需要我们教给学生的专业数据管理工具，这项任务的高社会价值将是激励。然后，学员将利用他们新的团队合作和综合技能，协作分析数据集。其结果将是新一代的科学家，他们接受过尖端的培训，拥有推进我们对全球变化的理解所需的历史数据。